MilaNLProc/survey-language-technologies huggingface dataset:
Gender: Female 
Age: 55-60
Nationality: United Kingdom;South Africa
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 5
Home: Other (Please specify) The house is owned by my husband
Employment: Employed full time
Occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Hobbies: Watch sports;Other (Please specify) Reading
Devices used daily: Smartphone;Other PC
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Grammar checker (i.e., correcting grammar mistakes) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT;Google Gemini 
LLM use cases: Writing (e.g., composing emails);Learning (e.g., explaining complex concepts in simple terms);Translation;Paraphrasing or finding synonyms 
Contexts of LLM use: Work;Personal 
Prompt 1: Write letter of complaint
Prompt 2: Write letter of resignation
Prompt 3: What to look for when buying binoculars
Prompt 4: How to identify planets and constellations
Prompt 5: Things to do in Mauritius
Prompt 6: How PayPal works
Prompt 7: Mother's Day poem
Prompt 8: Christmas day weather predictions for Cape Town
Gender: Female 
Age: 25-34
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 4
Home: Own 
Employment: Employed part time
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Skilled agricultural, forestry and fishery workers (those harvest, grow, breed, or produce a variety of animal husbandry products)
Hobbies: Exercise;Use social media;Do arts and crafts 
Devices used daily: Smartphone;Laptop;Smartwatch 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools they would find useful: Grammar checker (i.e., correcting grammar mistakes);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Writing (e.g., composing emails);Proofreading/Editing (e.g., grammar, spelling, structure improvements);Paraphrasing or finding synonyms;Summarizing long texts 
Contexts of LLM use: Work 
Prompt 1: Grammar and spell check the following text
Prompt 2: Find a synonym for always 
Prompt 3: Summarise the following text
Prompt 4: Generate reading comprehension questions for the following text for 10 year olds
Gender: Male 
Age: 25-34
Nationality: Canada
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 6
Home: Rent 
Employment: Employed part time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Father's occupation: Homemaker
Hobbies: Listen to hiphop and rap 
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools they would find useful: Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Coding 
Contexts of LLM use: Work;School/University 
Prompt 1: how to open a project in javascript
Prompt 2: how to handle get requests in javascript
Prompt 3: difference between node js and next js
Prompt 4: best stocks to invest in with low capital 2024
Prompt 5: write me a python script that handles asynchronous operations
Prompt 6: improve the text of my essay
Prompt 7: deploying a vercel project on a dev server
Prompt 8: give me some sample code of a Wasm package being called from a swift ios project. The wasm package would be embedded in the xcode project
Prompt 9: does \csvautotabular has any options?
Prompt 10: Write a short and sweet thank-you note to our babysitter for taking care of the kids this past weekend on a short notice. I want to let her know how much our whole family appreciates her!
Comments: Not really, I only really like to use them for programming as I find its useful when it's synced with the base.
Gender: Male 
Age: 35-44
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 4
Home: Rent 
Employment: Not employed, but looking for work
Occupation: Prefer not to say
Mother's occupation: Prefer not to say
Father's occupation: Prefer not to say
Hobbies: Listen to hiphop and rap;Listen to rock/indie music;Watch sports;Other (Please specify) Croquet - Golf - Video games
Devices used daily: Smartphone;Laptop 
NLP tools known: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools they would find useful: Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Writing (e.g., composing emails);Proofreading/Editing (e.g., grammar, spelling, structure improvements);Generate art 
Contexts of LLM use: Work;Personal 
Prompt 1: How can you establish an emotional connection with your audience through data storytelling? 150 words or less
Prompt 2: If I started a Food Truck Hub do you think it would be a good decision, answer truthfully and honestly
Prompt 3: write a review for a muic video with techno music while flying over an island
Prompt 4: In no more than 80 words, please describe your quantitative reasoning skills. team player and efficient
Prompt 5: synonym for deficit
Prompt 6: I want you to act as a professional blackjack player amd help me
Comments: Thanks!
Gender: Female 
Age: 55-60
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 6
Home: Own 
Employment: Employed part time
Occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Mother's occupation: Homemaker
Father's occupation: Armed forces occupations (includes all jobs held by members of the armed forces)
Hobbies: Visit to stately homes 
Devices used daily: Tablet;Smartphone;Laptop 
NLP tools known: Spell checker (i.e., correcting misspellings) 
NLP tools used: Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT 
LLM use cases: Brainstorming 
Contexts of LLM use: Work;Entertainment;Personal;Technical 
Prompt 1: Cooking 
Prompt 2: Transport 
Prompt 3: Flights 
Prompt 4: Holidays 
Prompt 5: Recipes 
Prompt 6: Decorating
Gender: Female 
Age: 60+
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Nothing 
Education: Doctorate or above
Mother's education: Graduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 9
Home: Own 
Employment: Self-employed part time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Homemaker
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Listen to classical music;Visit to stately homes;Use social media;Go to museums and galleries;Do arts and crafts 
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools they would find useful: Other (specify) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT 
LLM use cases: Generic chatbot conversation;Generate art 
Contexts of LLM use: Personal 
Prompt 1: Are you conscious?
Prompt 2: Why do you say you understand what I'm saying when you are just an LLM?
Gender: Male 
Age: 18-24
Nationality: United States;Poland
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English;Other (Please Specify) polish
Religion: Christian 
Education: Graduate degree
Mother's education: Undergraduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 6
Home: Own 
Employment: Employed full time
Occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Mother's occupation: Homemaker
Father's occupation: Armed forces occupations (includes all jobs held by members of the armed forces)
Hobbies: Listen to hiphop and rap;Listen to classical music;Exercise;Use social media;Go to museums and galleries;Watch sports;Attend football matches 
Devices used daily: Laptop;Smartphone;Tablet;Smartwatch 
NLP tools known: Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings) 
NLP tools used: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Grammar checker (i.e., correcting grammar mistakes);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools they would find useful: Grammar checker (i.e., correcting grammar mistakes) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT;Claude;Jasper;Google Gemini 
LLM use cases: Translation;Writing (e.g., composing emails);Paraphrasing or finding synonyms;Analyze data;Summarizing long texts 
Contexts of LLM use: School/University;Entertainment;Learning;Personal;Technical 
Prompt 1: Translate this text into Polish <photo>
Prompt 2: I want you to fill in these empty tables correctly.
Prompt 3: What is the difference between an inductor and a capacitor?
Prompt 4: What do the labels U, C, and D on a circuit diagram mean?
Prompt 5: What is a ground plane?
Prompt 6: What component controls a high current using a low current? What is it called?
Prompt 7: Explain Ohm's Law.
Prompt 8: How long can it take for a bill to pass through the Sejm?
Prompt 9: What happens if a bill reaches the Prime Minister?
Prompt 10: What is the purpose of flux in soldering?
Gender: Female 
Age: 60+
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 6
Home: Own 
Employment: Retired
Occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Listen to rock/indie music;Visit to stately homes;Exercise;Go to museums and galleries;Use social media;Other (Please specify) bird watching, walking
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools they would find useful: Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Never
Gender: Female 
Age: 25-34
Nationality: Nigeria
Ethnicity: Black or African American 
Marital status: Married 
First language: English 
Religion: Muslim 
Education: Graduate degree
Mother's education: Doctorate or above
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 5
Home: Rent 
Employment: Not employed and not looking for work
Occupation: Homemaker
Mother's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Father's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Hobbies: Use social media 
Devices used daily: Tablet;Smartphone;Laptop;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools used: Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT 
LLM use cases: Translation;Proofreading/Editing (e.g., grammar, spelling, structure improvements);Get information about current events;Learning (e.g., explaining complex concepts in simple terms);Completing assignments 
Contexts of LLM use: Work;School/University;Learning;Personal;Entertainment 
Prompt 1: List of Environmental organisations in the uk
Prompt 2: Can you help me draft a Christmas wishes wordings for my son’s class teacher
Prompt 3: What are the qualities of a good customer service advisor 
Prompt 4: Business ideas to invest on in the uk
Prompt 5: Where are the beautiful places to visit in canada
Prompt 6: Can you help me plan a vacation on a budget
Prompt 7: Why does my 1 year old have a running nose all the time
Prompt 8: When is best time to visit Paris
Prompt 9: Can you sum up this arithmetic for me please? £75.40+£2.89+0.14
Prompt 10: What are the four seasons we have in the uk and what month do they fall in
Gender: Female 
Age: 18-24
Nationality: Canada
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Student
Occupation: Prefer not to say
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Plant and machine operators, and assemblers (those who maintain, operate and monitor industrial and agricultural machinery and equipment)
Hobbies: Do arts and crafts;Watch sports;Exercise;Use social media 
Devices used daily: Smartphone;Tablet;Smartwatch;Other desktop
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
NLP tools used: Text-to-Speech (i.e, computers being able to read out loud written language);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Brainstorming;Answering questions about general knowledge;Learning (e.g., explaining complex concepts in simple terms) 
Contexts of LLM use: Personal;School/University;Creative or artistic 
Prompt 1: what are some bookish sticker design ideas
Prompt 2: What are some bookish sayings from booktok
Prompt 3: Sticker idea with a candle and bookish quote
Prompt 4: An essay outline for an essay analyzing Jane eyre using lacan’s mirror stage theory
Prompt 5: what are the main points in Lacan's essay "the agency of the letter in the unconscious or reason"
Prompt 6: how is Lacan's mirror stage represented in Jane eyre
Prompt 7: why does lacan say that culture does not exist
Prompt 8: what does zizek mean when he says If we preserve an intimate distance toward the “social role we play”, we doubly deceive ourselves
Prompt 9: what are some discussion questions about zizek's article "how the un-duped err:
Prompt 10: what period followed the harrappan period
Gender: Male 
Age: 35-44
Nationality: Canada
Ethnicity: Black or African American 
Marital status: Cohabitating 
First language: English 
Religion: Christian 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Not employed, unable to work due to a disability or illness
Occupation: Prefer not to say
Mother's occupation: Homemaker
Father's occupation: Craft related trades workers (those who produce or process foodstuffs, textiles, wooden, metal and other articles, including handicraft goods, and apply specific technical and practical knowledge and skills to construct and maintain buildings)
Hobbies: Listen to hiphop and rap;Listen to classical music;Use social media;Other (Please specify) play video games
Devices used daily: Smartphone 
NLP tools known: Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Spell checker (i.e., correcting misspellings) 
NLP tools used: Text-to-Speech (i.e, computers being able to read out loud written language);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT 
Prompt 1: ey chat gpt create an image of megman x and zero
Prompt 2: Give me a clan name that starts with blood
Prompt 3: This past week i was playing video games with my best friend corey
Prompt 4: what took place during the J FK assiassination
Comments: none
Gender: Male 
Age: 60+
Nationality: United Kingdom
Marital status: Married 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Retired
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Exercise;Listen to rock/indie music;Watch sports;Attend football matches;Go to museums and galleries;Use social media 
Devices used daily: Tablet;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Text-to-Speech (i.e, computers being able to read out loud written language);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
NLP tools used: Spell checker (i.e., correcting misspellings);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT;Google Gemini;GitHub Copilot 
LLM use cases: Translation;Writing (e.g., composing emails);Generic chatbot conversation;Answering questions about general knowledge 
Contexts of LLM use: Learning;Personal 
Prompt 1: I can't recall the specifics
Prompt 2: I have used for translations and general questions
Comments: I am finding them more and more useful and quite surprised how accurate and relevant the provided information is.
Gender: Female 
Age: 60+
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Retired
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Homemaker
Father's occupation: Plant and machine operators, and assemblers (those who maintain, operate and monitor industrial and agricultural machinery and equipment)
Hobbies: Visit to stately homes;Listen to classical music;Other (Please specify) Church activities
Devices used daily: Laptop;Tablet;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings) 
NLP tools used: Spell checker (i.e., correcting misspellings) 
Frequency of LLM use: Never
Comments: I am interested in AI chatbots although I do not use them personally I have had access via Prolific Studies.
Gender: Female 
Age: 35-44
Nationality: Nigeria;Sweden
Ethnicity: Black or African American 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: Graduate degree
Father's education: Graduate degree
Self-assessed socioeconomic status (1-10): 8
Home: Rent 
Employment: Employed part time
Occupation: Skilled agricultural, forestry and fishery workers (those harvest, grow, breed, or produce a variety of animal husbandry products)
Mother's occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Father's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Hobbies: Listen to classical music;Use social media 
Devices used daily: Laptop;Tablet;Smartphone 
NLP tools known: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools used: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT;Snapchat My AI 
LLM use cases: Translation;Paraphrasing or finding synonyms;Collecting references 
Contexts of LLM use: Entertainment;Personal 
Prompt 1: Content on kids clothing
Prompt 2: Advert plan on water bottle
Prompt 3: references on a research
Prompt 4: Explanation about a financial company 
Prompt 5: What is communication skill
Prompt 6: Barriers of good communication 
Prompt 7: Romantic messages I can learn
Gender: Male 
Age: 60+
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: Graduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 4
Home: Own 
Employment: Retired
Mother's occupation: Homemaker
Father's occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Hobbies: Listen to rock/indie music;Listen to jazz;Watch sports;Do arts and crafts;Exercise;Other (Please specify) Read
Devices used daily: Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
Frequency of LLM use: Rarely
Contexts of LLM use: Technical 
Prompt 1: Checking Internet error
Prompt 2: Following instructions to remedy Internet errors
Prompt 3: Booking Internet engineer
Prompt 4: Ordering on line
Comments: Sometimes it is difficult knowing whether I am using an AI chatbit or not
Gender: Female 
Age: 45-54
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Christian 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 6
Home: Own 
Employment: Retired
Occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Mother's occupation: Homemaker
Father's occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Hobbies: Exercise;Use social media;Do arts and crafts 
Devices used daily: Smartphone;Tablet;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Grammar checker (i.e., correcting grammar mistakes);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Rarely
LLMs used: None of these 
LLM use cases: Translation 
Contexts of LLM use: Learning
Gender: Female 
Age: 35-44
Nationality: Canada
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: Undergraduate degree
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Not employed, unable to work due to a disability or illness
Occupation: Prefer not to say
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Hobbies: Listen to rock/indie music;Exercise;Go to museums and galleries;Do arts and crafts;Other (Please specify) read, paint
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Spell checker (i.e., correcting misspellings) 
NLP tools used: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Grammar checker (i.e., correcting grammar mistakes) 
NLP tools they would find useful: E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT;Google Bard 
LLM use cases: Generate art;Translation;Brainstorming;Answering questions about general knowledge 
Contexts of LLM use: Entertainment;Creative or artistic 
Prompt 1: English to pirate translation
Prompt 2: how to cook steak
Prompt 3: how to sear stake in pan
Prompt 4: how to cook steak in oven
Prompt 5: modern English to midevil English translation
Prompt 6: Toronto landscape with modern elements with saturated neon colors
Prompt 7: can you mix reitonl with aha ?
Gender: Male 
Age: 60+
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Divorced 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 4
Home: Rent 
Employment: Retired
Occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Mother's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Father's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Hobbies: Listen to classical music;Go to the opera;Visit to stately homes;Exercise;Go to museums and galleries;Watch sports 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder) 
NLP tools they would find useful: Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
Frequency of LLM use: Never
Comments: I HAVE NEVER USED THE AND I DOUBT THAT I EVER SHALL
Gender: Female 
Age: 60+
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Employed full time
Occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Mother's occupation: Homemaker
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Listen to classical music;Exercise;Go to museums and galleries 
Devices used daily: Laptop;Smartphone;Tablet;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools they would find useful: Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Writing (e.g., composing emails);Answering questions about general knowledge 
Contexts of LLM use: Work;Personal 
Prompt 1: What should I do if I think I have an eye infection
Gender: Female 
Age: 60+
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Employed full time
Occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Mother's occupation: Homemaker
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Listen to classical music;Exercise;Go to museums and galleries 
Devices used daily: Laptop;Tablet;Smartphone;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
NLP tools they would find useful: Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Writing (e.g., composing emails) 
Contexts of LLM use: Work;Personal 
Prompt 1: What should I do if I think I have an eye infection
Prompt 2: write a letter of complaint to Tesco that their product, supersweet sweetcorn is below quality.  Its skin is waxy, tough and old.  I would like a refund.
Prompt 3: How do I know if I am adopted
Prompt 4: how to I change the cabin filter in my car
Gender: Female 
Age: 45-54
Nationality: Canada
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Christian 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 4
Home: Rent 
Employment: Employed part time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Plant and machine operators, and assemblers (those who maintain, operate and monitor industrial and agricultural machinery and equipment)
Father's occupation: Plant and machine operators, and assemblers (those who maintain, operate and monitor industrial and agricultural machinery and equipment)
Hobbies: Exercise;Listen to classical music;Other (Please specify) family game night, walking, watch tv, cook, bake, listen to dance, 
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Other (specify) writing poems and general information
Contexts of LLM use: Entertainment;Personal;Creative or artistic writing poems , general information, recipes 
Prompt 1: old fashioned banana bread recipe
Prompt 2: how to care for fresh cut flowers
Prompt 3: how to care for real christmas tree
Prompt 4: can you please write a Christmas poem about my mother if she were here add in her excitement for the presents, the food, add in all the excitement for the presents, the food, her grandchildren, and great grandchirldren , remembering the biggest smile and the love that she would feel in my house , the christmas magic, wishing she were still here, and that ive kept her traditions alive, that she is foever
Gender: Male 
Age: 45-54
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Cohabitating 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 4
Home: Other (Please specify) Shared ownership
Employment: Employed part time
Occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Mother's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Father's occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Hobbies: Listen to rock/indie music;Listen to hiphop and rap;Use social media;Watch sports 
Devices used daily: Laptop;Smartphone 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools they would find useful: Dialog technology (e.g. chatbots that communicate with you such as chatGPT) 
Frequency of LLM use: Rarely
LLMs used: ChatGPT 
LLM use cases: Digital content creation (e.g., creation of social media content);Generate art